Construction and Clinical Relevance of a Predictive Model of Coronary Microcirculatory Dysfunction in Patients With Acute Myocardial Infarction Following Percutaneous Coronary Intervention - Shuai Wang; Yuanyuan Zhao; Yanlong Zhao; Yanling Wang; Zhenxing Fan; Zhi Liu (Reviews in Cardiovascular Medicine)
Background: Coronary microcirculatory dysfunction (CMD) after percutaneous coronary intervention (PCI) in patients suffering from acute myocardial infarction (AMI) may adversely affect prognosis. The objective of this study was to assess the postoperative microcirculatory status and to construct a predictive model for CMD. Methods: This study is a retrospective analysis of 187 AMI patients who underwent PCI at Xuanwu Hospital. Patients were divided into two cohorts based on postoperative angiography-derived microcirculatory resistance (AMR) values: a non-CMD group (AMR <250 mmHg*s/m, n = 93) and a CMD group (AMR ≥250 mmHg*s/m, n = 76). Clinical and laboratory data were extracted, predictive models were constructed and risk factors associated with CMD were identified through the implementation of LASSO regression analyses. Results: The non-CMD group (n = 93) had a significantly lower body mass index (BMI) (25.40 ± 2.84) and a higher proportion of males (91.4%) compared to the non-CMD group (n = 76) (BMI: 26.64 ± 3.74, p < 0.05; males: 78.9%, p < 0.05). The non-CMD group also exhibited lower Creatine Kinase (CK) levels, glucose levels (GLU), mean platelet volume (MPV), and platelet distribution width (PDW). LASSO regression identified significant predictors of CMD after PCI in AMI patients. A nomogram showed excellent predictive performance (area under curve (AUC): 0.737) and higher net benefit compared to individual models. Conclusion: The predictive model developed in this study effectively identifies the risk of microcirculatory dysfunction in AMI patients after PCI, providing important insights for clinical decision-making. Future research should further validate the external applicability of this model and explore its potential in clinical practice. Clinical Trial Registration: NCT06062316, https://clinicaltrials.gov/study/NCT06062316?term=NCT06062316&rank=1, registration time: December 21, 2023.